To understand the mechanisms of ageing in Saccharomyces cerevisiae (budding yeast), a variety of experimental and computational approaches can be used, targeting the two main ageing paradigms: replicative lifespan (RLS) and chronological lifespan (CLS).
1. Define the Ageing Paradigm
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Replicative Lifespan (RLS): Number of daughter cells a mother cell can produce before senescence.
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Chronological Lifespan (CLS): Length of time non-dividing yeast cells remain viable in stationary phase.
Depending on your focus (RLS or CLS), you’ll choose different tools and assays.
2. Experimental Approaches
A. Microscopy and Microdissection (RLS)
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Method: Track single mother cells using micromanipulation or microfluidic devices to count the number of divisions.
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Goal: Identify age-related phenotypes such as changes in morphology, size, vacuolar fragmentation, and cell wall thickening.
B. Survival Assays (CLS)
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Method: Grow yeast to stationary phase, then periodically assess viability by colony-forming units (CFUs) or dye exclusion (e.g., propidium iodide).
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Goal: Understand how metabolic state, oxidative stress, and autophagy affect longevity.
C. Genomic Screens
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Knockout/Overexpression Screens:
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Use the yeast deletion collection or overexpression libraries to find genes that extend or shorten lifespan.
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Analyze hits to identify conserved pathways (e.g., TOR, sirtuins, mitochondrial function).
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CRISPR-based screens: Modern alternative for more precise gene perturbation.
D. Transcriptomics and Proteomics
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RNA-Seq or Microarrays: Profile changes in gene expression during ageing.
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Proteomics: Quantify age-associated protein abundance, post-translational modifications, or aggregation.
E. Metabolomics and Lipidomics
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Mass Spectrometry or NMR: Investigate metabolic shifts with age, such as NAD+ levels, ROS accumulation, or lipid peroxidation.
F. Epigenetic and Chromatin Analyses
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ChIP-seq: Examine histone modifications and chromatin structure over time.
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Focus: Silencing at rDNA loci and telomeres, which are key in yeast ageing.
G. Organelle-Specific Studies
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Mitochondrial Function:
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Assess membrane potential, ROS production, and mitochondrial inheritance.
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Vacuole Function:
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pH maintenance, autophagy, and storage—critical for long-term survival.
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3. Computational Approaches
A. Network Analysis
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Integrate genomic, transcriptomic, and proteomic data to build gene-regulatory or protein-protein interaction networks.
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Identify hub genes or pathways associated with ageing.
B. Machine Learning
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Use time-course omics data to predict key regulators or biomarkers of ageing.
C. Comparative Genomics
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Compare ageing-associated genes across yeast species or between yeast and higher eukaryotes to identify conserved ageing mechanisms.
4. Perturbation Experiments
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Environmental Manipulations:
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Caloric restriction (CR), oxidative stress, or chemical inhibitors (e.g., rapamycin).
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Genetic Perturbations:
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Overexpress or delete genes like SIR2, TOR1, RPL31, or mitochondrial genes to study their impact on lifespan.
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5. Emerging Techniques
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Single-cell RNA-seq: Explore heterogeneity in ageing populations.
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Microfluidics: Real-time tracking of RLS in high-throughput manner.
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Live-cell biosensors: Measure intracellular pH, ROS, or NAD+/NADH ratios dynamically.
Summary
A comprehensive approach would combine:
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Microscopy for phenotypic observations
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High-throughput genetic screens
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Omics profiling (transcriptomics, proteomics, metabolomics)
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Functional studies of mitochondria, autophagy, and epigenetics
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Computational modeling and network analysis
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